A new automatic method capable of registering multimodal images like terrain maps and multispectral data is presented. In order to speed up the processing, given the large amount of data typical of such settings, the method exploits a multi-resolution approach, which may select different similarity measures in consideration of image resolution and size. In fact, the performances of Cross Correlation and Maximization of Mutual Information (MMI) on images of different resolution and size have been evaluated and are described The adaptive strategy adopted is designed to exploit the strengths and to overcome the limitations of the similarity criteria employed. In case multimodal views are to be registered on 3D models, MMI is to be preferred. The strategies to improve its performance also on smaller images are presented.
Automatic registration of multimodal views on large aerial images
F. Uccheddu;
2012
Abstract
A new automatic method capable of registering multimodal images like terrain maps and multispectral data is presented. In order to speed up the processing, given the large amount of data typical of such settings, the method exploits a multi-resolution approach, which may select different similarity measures in consideration of image resolution and size. In fact, the performances of Cross Correlation and Maximization of Mutual Information (MMI) on images of different resolution and size have been evaluated and are described The adaptive strategy adopted is designed to exploit the strengths and to overcome the limitations of the similarity criteria employed. In case multimodal views are to be registered on 3D models, MMI is to be preferred. The strategies to improve its performance also on smaller images are presented.
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